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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_edauni.wasp
Title produced by softwareUnivariate Explorative Data Analysis
Date of computationSat, 04 Dec 2010 10:09:17 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/04/t12914572607dbb4v4m5xhqqkr.htm/, Retrieved Sat, 04 May 2024 12:44:41 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=105068, Retrieved Sat, 04 May 2024 12:44:41 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact156
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Central Tendency] [SHW_WS3_Yt=c+Xt] [2009-10-16 08:10:06] [8b1aef4e7013bd33fbc2a5833375c5f5]
- RMPD  [Univariate Explorative Data Analysis] [] [2009-11-02 10:43:25] [8b1aef4e7013bd33fbc2a5833375c5f5]
-   PD      [Univariate Explorative Data Analysis] [Paper univariate 2] [2010-12-04 10:09:17] [da925928e5a77063c5ecc7b801d712e1] [Current]
- R  D        [Univariate Explorative Data Analysis] [] [2011-12-01 18:21:13] [74be16979710d4c4e7c6647856088456]
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Dataseries X:
-2,250815803
-2,250025575
-2,248469388
-2,249602446
-2,248990826
-2,24598369
-2,245779817
-2,245380711
-2,243004552
-2,245
-2,244359233
-2,247455919
-2,248922457
-2,248721805
-2,24955
-2,246140089
-2,244470821
-2,245559389
-2,246977887
-2,246879607
-2,248921569
-2,248486036
-2,249574156
-2,249339853
-2,245839844
-2,247176987
-2,247019932
-2,251234867
-2,253571774
-2,255750845
-2,253840231
-2,253942308
-2,253956835
-2,253815916
-2,254736842
-2,253448111
-2,254229852
-2,251706387
-2,251615055
-2,252952381
-2,255066414
-2,252336802
-2,252961738
-2,251556604
-2,251517436
-2,252561205
-2,251263504
-2,251846298
-2,252559663
-2,25411215
-2,254727018
-2,251061453
-2,247860465
-2,249532191
-2,248863216
-2,249580452
-2,250653775
-2,246850575
-2,248297384
-2,24959193
-2,249661482
-2,248259479
-2,246000912
-2,247477314
-2,248637392
-2,247013575
-2,245843102
-2,245990991
-2,245778578
-2,248898876
-2,248470166
-2,247046168




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time15 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 15 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=105068&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]15 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=105068&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=105068&T=0

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time15 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Descriptive Statistics
# observations72
minimum-2.255750845
Q1-2.25174136475
median-2.2491653395
mean-2.24951566811111
Q3-2.24701834275
maximum-2.243004552

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics \tabularnewline
# observations & 72 \tabularnewline
minimum & -2.255750845 \tabularnewline
Q1 & -2.25174136475 \tabularnewline
median & -2.2491653395 \tabularnewline
mean & -2.24951566811111 \tabularnewline
Q3 & -2.24701834275 \tabularnewline
maximum & -2.243004552 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=105068&T=1

[TABLE]
[ROW][C]Descriptive Statistics[/C][/ROW]
[ROW][C]# observations[/C][C]72[/C][/ROW]
[ROW][C]minimum[/C][C]-2.255750845[/C][/ROW]
[ROW][C]Q1[/C][C]-2.25174136475[/C][/ROW]
[ROW][C]median[/C][C]-2.2491653395[/C][/ROW]
[ROW][C]mean[/C][C]-2.24951566811111[/C][/ROW]
[ROW][C]Q3[/C][C]-2.24701834275[/C][/ROW]
[ROW][C]maximum[/C][C]-2.243004552[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=105068&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=105068&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Descriptive Statistics
# observations72
minimum-2.255750845
Q1-2.25174136475
median-2.2491653395
mean-2.24951566811111
Q3-2.24701834275
maximum-2.243004552



Parameters (Session):
par1 = 0 ; par2 = 0 ;
Parameters (R input):
par1 = 0 ; par2 = 0 ;
R code (references can be found in the software module):
par1 <- as.numeric(par1)
par2 <- as.numeric(par2)
x <- as.ts(x)
library(lattice)
bitmap(file='pic1.png')
plot(x,type='l',main='Run Sequence Plot',xlab='time or index',ylab='value')
grid()
dev.off()
bitmap(file='pic2.png')
hist(x)
grid()
dev.off()
bitmap(file='pic3.png')
if (par1 > 0)
{
densityplot(~x,col='black',main=paste('Density Plot bw = ',par1),bw=par1)
} else {
densityplot(~x,col='black',main='Density Plot')
}
dev.off()
bitmap(file='pic4.png')
qqnorm(x)
qqline(x)
grid()
dev.off()
if (par2 > 0)
{
bitmap(file='lagplot1.png')
dum <- cbind(lag(x,k=1),x)
dum
dum1 <- dum[2:length(x),]
dum1
z <- as.data.frame(dum1)
z
plot(z,main='Lag plot (k=1), lowess, and regression line')
lines(lowess(z))
abline(lm(z))
dev.off()
if (par2 > 1) {
bitmap(file='lagplotpar2.png')
dum <- cbind(lag(x,k=par2),x)
dum
dum1 <- dum[(par2+1):length(x),]
dum1
z <- as.data.frame(dum1)
z
mylagtitle <- 'Lag plot (k='
mylagtitle <- paste(mylagtitle,par2,sep='')
mylagtitle <- paste(mylagtitle,'), and lowess',sep='')
plot(z,main=mylagtitle)
lines(lowess(z))
dev.off()
}
bitmap(file='pic5.png')
acf(x,lag.max=par2,main='Autocorrelation Function')
grid()
dev.off()
}
summary(x)
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Descriptive Statistics',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'# observations',header=TRUE)
a<-table.element(a,length(x))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'minimum',header=TRUE)
a<-table.element(a,min(x))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Q1',header=TRUE)
a<-table.element(a,quantile(x,0.25))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'median',header=TRUE)
a<-table.element(a,median(x))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'mean',header=TRUE)
a<-table.element(a,mean(x))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Q3',header=TRUE)
a<-table.element(a,quantile(x,0.75))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'maximum',header=TRUE)
a<-table.element(a,max(x))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')